Epigenetic dysregulation in cancers by isocitrate dehydrogenase 2 (IDH2).

Recent advances in genome-wide studies have revealed numerous epigenetic regulations brought about by genes involved in cellular metabolism. Isocitrate dehydrogenase (IDH), an essential enzyme, that converts isocitrate into -ketoglutarate (KG) predominantly in the tricarboxylic acid (TCA) cycle, has gained particular importance due to its cardinal role in the metabolic pathway in cells. IDH1, IDH2, and IDH3 are the three isomeric IDH enzymes that have been shown to regulate cellular metabolism. Of particular importance, IDH2 genes are associated with several cancers, including gliomas, oligodendroglioma, and astrocytomas. These mutations lead to the production of oncometabolite D-2-hydroxyglutarate (D-2-HG), which accumulates in cells promoting tumor growth. The enhanced levels of D-2-HG competitively inhibit α-KG dependent enzymes, inhibiting cell TCA cycle, upregulating the cell growth and survival relevant HIF-1α pathway, promoting DNA hypermethylation related epigenetic activity, all of which synergistically contribute to carcinogenesis. The present review discusses epigenetic mechanisms inIDH2 regulation in cells and further its clinical implications.

Potential inhibitors of VEGFR1, VEGFR2, and VEGFR3 developed through Deep Learning for the treatment of Cervical Cancer.

Cervical cancer stands as a prevalent gynaecologic malignancy affecting women globally, often linked to persistent human papillomavirus infection. Biomarkers associated with cervical cancer, including VEGF-A, VEGF-B, VEGF-C, VEGF-D, and VEGF-E, show upregulation and are linked to angiogenesis and lymphangiogenesis. This research aims to employ in-silico methods to target tyrosine kinase receptor proteins-VEGFR-1, VEGFR-2, and VEGFR-3, and identify novel inhibitors for Vascular Endothelial Growth Factors receptors (VEGFRs). A comprehensive literary study was conducted which identified 26 established inhibitors for VEGFR-1, VEGFR-2, and VEGFR-3 receptor proteins. Compounds with high-affinity scores, including PubChem ID-25102847, 369976, and 208908 were chosen from pre-existing compounds for creating Deep Learning-based models. RD-Kit, a Deep learning algorithm, was used to generate 43 million compounds for VEGFR-1, VEGFR-2, and VEGFR-3 targets. Molecular docking studies were conducted on the top 10 molecules for each target to validate the receptor-ligand binding affinity. The results of Molecular Docking indicated that PubChem IDs-71465,645 and 11152946 exhibited strong affinity, designating them as the most efficient molecules. To further investigate their potential, a Molecular Dynamics Simulation was performed to assess conformational stability, and a pharmacophore analysis was also conducted for indoctrinating interactions.

Unveiling the ESR1 Conformational Stability and Screening Potent Inhibitors for Breast Cancer Treatment

BACKGROUND: The current study recognizes the significance of estrogen receptor alpha (ERα) as a member of the nuclear receptor protein family, which holds a central role in the pathophysiology of breast cancer. ERα serves as a valuable prognostic marker, with its established relevance in predicting disease outcomes and treatment responses. METHOD: In this study, computational methods are utilized to search for suitable drug-like compounds that demonstrate analogous ligand binding kinetics to ERα. RESULTS: Docking-based simulation screened out the top 5 compounds - ZINC13377936, NCI35753, ZINC35465238, ZINC14726791, and NCI663569 against the targeted protein. Further, their dynamics studies reveal that the compounds ZINC13377936 and NCI35753 exhibit the highest binding stability and affinity. CONCLUSION: Anticipating the competitive inhibition of ERα protein expression in breast cancer, we envision that both ZINC13377936 and NCI35753 compounds hold substantial promise as potential therapeutic agents. These candidates warrant thorough consideration for rigorous In vitro and In vivo evaluations within the context of clinical trials. The findings from this current investigation carry significant implications for the advancement of future diagnostic and therapeutic approaches for breast cancer.

Transcriptional regulatory mechanisms and signaling networks in cancer.

Cancer is a general term that refers to a wide range of illnesses that are characterized by the development of aberrant cells that have the capacity to divide uncontrollably, invade, and harm healthy tissue. It is caused by both genetic and epigenetic changes that suppress abnormal proliferation and prevent cells from surviving outside of their normal niches. Complex protein networks are responsible for the development of a suitable environment via multiple cells signaling pathways. The study of these pathways is essential for analysing network context and developing novel cancer therapies. Transcription factors (TFs) are actively involved in gene expression and maintain the combinatorial on-and-off states of the gene. In addition, the TFs regulate cell identity and state; these TFs cooperate to establish cell-type-specific gene expression. In this chapter, we describe the number of transcription factors and their role in the progression of cancer. The knowledge of transcriptional factors and their network is crucial for emphasizing the specific transcriptional addiction and for designing new anticancer therapies.

Structure-Based Virtual Screening, Molecular Docking, Molecular Dynamics Simulation of EGFR for the Clinical Treatment of Glioblastoma.

Glioblastoma (GBM) is a WHO Grade IV tumor with poor visibility, a high risk of comorbidity, and exhibit limited treatment options. Resurfacing from second-rate glioma was originally classified as either mandatory or optional. Recent interest in personalized medicine has motivated research toward biomarker stratification-based individualized illness therapy. GBM biomarkers have been investigated for their potential utility in prognostic stratification, driving the development of targeted therapy and customizing therapeutic treatment. Due to the availability of a specific EGFRvIII mutational variation with a clear function in glioma-genesis, recent research suggests that EGFR has the potential to be a prognostic factor in GBM, while others have shown no clinical link between EGFR and survival. The pre-existing pharmaceutical lapatinib (PubChem ID: 208,908) with a higher affinity score is used for virtual screening. As a result, the current study revealed a newly screened chemical (PubChem CID: 59,671,768) with a higher affinity than the previously known molecule. When the two compounds are compared, the former has the lowest re-rank score. The time-resolved features of a virtually screened chemical and an established compound were investigated using molecular dynamics simulation. Both compounds are equivalent, according to the ADMET study. This report implies that the virtual screened chemical could be a promising Glioblastoma therapy.

Exploring the macromolecules for secretory pathway in cancer disease.

Secretory proteins play an important role in the tumor microenvironment and are widely distributed throughout tumor tissues. Tumor cells secrete a protein that mediates communication between tumor cells and stromal cells, thereby controlling tumor growth and affecting the success of cancer treatments in the clinic. The cancer secretome is produced by various secretory pathways and has a wide range of applications in oncoproteomics. Secretory proteins are involved in cancer development and tumor cell migration, and thus serve as biomarkers or effective therapeutic targets for a variety of cancers. Several proteomic strategies have recently been used for the analysis of cancer secretomes in order to gain a better understanding and elaborate interpretation. For instance, the development of exosome proteomics, degradomics, and tumor-host cell interaction provide clear information regarding the mechanism of cancer pathobiology. In this chapter, we emphasize the recent advances in secretory protein and the challenges in the field of secretome analysis and their clinical applications.

Unraveling the multi-targeted curative potential of bioactive molecules against cervical cancer through integrated omics and systems pharmacology approach.

Molecular level understanding on the role of viral infections causing cervical cancer is highly essential for therapeutic development. In these instances, systems pharmacology along with multi omics approach helps in unraveling the multi-targeted mechanisms of novel biologically active compounds to combat cervical cancer. The immuno-transcriptomic dataset of healthy and infected cervical cancer patients was retrieved from the array express. Further, the phytocompounds from medicinal plants were collected from the literature. Network Analyst 3.0 has been used to identify the immune genes around 384 which are differentially expressed and responsible for cervical cancer. Among the 87 compounds reported in plants for treating cervical cancer, only 79 compounds were targeting the identified immune genes of cervical cancer. The significant genes responsible for the domination in cervical cancer are identified in this study. The virogenomic signatures observed from cervical cancer caused by E7 oncoproteins serve as the potential therapeutic targets whereas, the identified compounds can act as anti-HPV drug deliveries. In future, the exploratory rationale of the acquired results will be useful in optimizing small molecules which can be a viable drug candidate.

Integrated Transcriptome Profiling Identifies Prognostic Hub Genes as Therapeutic Targets of Glioblastoma: Evidenced by Bioinformatics Analysis.

Glioblastoma (GBM) is the most devastating and frequent type of primary brain tumor with high morbidity and mortality. Despite the use of surgical resection followed by radio- and chemotherapy as standard therapy, the progression of GBM remains dismal with a median overall survival of <15 months. GBM embodies a populace of cancer stem cells (GSCs) that is associated with tumor initiation, invasion, therapeutic resistance, and post-treatment reoccurrence. However, understanding the potential mechanisms of stemness and their candidate biomarkers remains limited. Hence in this investigation, we aimed to illuminate potential candidate hub genes and key pathways associated with the pathogenesis of GSC in the development of GBM. The integrated analysis discovered differentially expressed genes (DEGs) between the brain cancer tissues (GBM and GSC) and normal brain tissues. Multiple approaches, including gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, were employed to functionally annotate the DEGs and visualize them through the R program. The significant hub genes were identified through the protein-protein interaction network, Venn diagram analysis, and survival analysis. We observed that the upregulated DEGs were prominently involved in the ECM-receptor interaction pathway. The downregulated genes were mainly associated with the axon guidance pathway. Five significant hub genes (CTNNB1, ITGB1, TNC, EGFR, and SHOX2) were screened out through multiple analyses. GO and KEGG analyses of hub genes uncovered that these genes were primarily enriched in disease-associated pathways such as the inhibition of apoptosis and the DNA damage repair mechanism, activation of the cell cycle, EMT (epithelial-mesenchymal transition), hormone AR (androgen receptor), hormone ER (estrogen receptor), PI3K/AKT (phosphatidylinositol 3-kinase and AKT), RTK (receptor tyrosine kinase), and TSC/mTOR (tuberous sclerosis complex and mammalian target of rapamycin). Consequently, the epigenetic regulatory network disclosed that hub genes played a vital role in the progression of GBM. Finally, candidate drugs were predicted that can be used as possible drugs to treat GBM patients. Overall, our investigation offered five hub genes (CTNNB1, ITGB1, TNC, EGFR, and SHOX2) that could be used as precise diagnostic and prognostic candidate biomarkers of GBM and might be used as personalized therapeutic targets to obstruct gliomagenesis.

Structure and chemistry of enzymatic active sites that play a role in the switch and conformation mechanism.

Enzymes, which are biological molecules, are constructed from polypeptide chains, and these molecules are activated through reaction mechanisms. It is the role of enzymes to speed up chemical reactions that are used to build or break down cell structures. Activation energy is reduced by the enzymes' selective binding of substrates in a protected environment. In enzyme tertiary structures, the active sites are commonly situated in a "cleft," which necessitates the diffusion of substrates and products. The amino acid residues of the active site may be far apart in the primary structure owing to the folding required for tertiary structure. Due to their critical role in substrate binding and attraction, changes in amino acid structure at or near the enzyme's active site usually alter enzyme activity. At the enzyme's active site, or where the chemical reactions occur, the substrate is bound. Enzyme substrates are the primary targets of the enzyme's active site, which is designed to assist in the chemical reaction. This chapter elucidates the summary of structure and chemistry of enzymes, their active site features, charges and role of water in the structures to clarify the biochemistry of the enzymes in the depth of atomic features.

Structure-Based Virtual Screening, Molecular Docking, and Molecular Dynamics Simulation of VEGF inhibitors for the clinical treatment of Ovarian Cancer.

Vascular endothelial growth factor (VEGF) and its receptor play an important role both in physiologic and pathologic angiogenesis, which is identified in ovarian cancer progression and metastasis development. The aim of the present investigation is to identify a potential vascular endothelial growth factor inhibitor which is playing a crucial role in stimulating the immunosuppressive microenvironment in tumor cells of the ovary and to examine the effectiveness of the identified inhibitor for the treatment of ovarian cancer using various in silico approaches. Twelve established VEGF inhibitors were collected from various literatures. The compound AEE788 displays great affinity towards the target protein as a result of docking study. AEE788 was further used for structure-based virtual screening in order to obtain a more structurally similar compound with high affinity. Among the 80 virtual screened compounds, CID 88265020 explicates much better affinity than the established compound AEE788. Based on molecular dynamics simulation, pharmacophore and comparative toxicity analysis of both the best established compound and the best virtual screened compound displayed a trivial variation in associated properties. The virtual screened compound CID 88265020 has a high affinity with the lowest re-rank score and holds a huge potential to inhibit the VGFR and can be implemented for prospective future investigations in ovarian cancer.

Immunological insights of selectins in human disease mechanism.

Selectin enzymes are glycoproteins and are an important adhesion molecule in the mammalian immune system, especially in the inflammatory response and the healing process of tissues. Selectins play an important role in a variety of biological processes, including the rolling of leukocytes in endothelial cells, a process known as the adhesion cascade. It has recently been discovered and reported that the selectin mechanism plays a role in cancer and thrombosis disease. This process begins with non-covalent interactions-based selectin-ligand binding and the glycans play a role as a connector between cancer cells and the endothelium in this process. The selectin mechanism is critical for the immune system, but it is also involved in disease mechanisms, earning the selectins the nickname "Selectins-The Two Dr. Jekyll and Mr. Hyde Faces". As a result, the drug for selectins should have a multifaceted role and be a dynamic molecule that targets the disease mechanism specifically. This chapter explores the role of selectins in the disease mechanism at the mechanism level that provides the impact for identifying the selectin inhibitors. Overall, this chapter provides the molecular level insights on selectins, their ligands, involvement in normal and disease mechanisms.

In silico identification of natural product inhibitors against Octamer-binding transcription factor 4 (Oct4) to impede the mechanism of glioma stem cells.

Octamer-binding transcription factor 4 (Oct4) is a core regulator in the retention of stemness, invasive, and self-renewal properties in glioma initiating cells (GSCs) and its overexpression inhibits the differentiation of glioma cells promoting tumor cell proliferation. The Pit-Oct-Unc (POU) domain comprising POU-specific domain (POUS) and POU-type homeodomain (POUHD) subdomains is the most critical part of the Oct4 for the generation of induced pluripotent stem cells from somatic cells that lead to tumor initiation, invasion, posttreatment relapse, and therapeutic resistance. Therefore, the present investigation hunts for natural product inhibitors (NPIs) against the POUHD domain of Oct4 by employing receptor-based virtual screening (RBVS) followed by binding free energy calculation and molecular dynamics simulation (MDS). RBVS provided 13 compounds with acceptable ranges of pharmacokinetic properties and good docking scores having key interactions with the POUHD domain. More Specifically, conformational and interaction stability analysis of 13 compounds through MDS unveiled two compounds ZINC02145000 and ZINC32124203 which stabilized the backbone of protein even in the presence of linker and POUS domain. Additionally, ZINC02145000 and ZINC32124203 exhibited stable and strong interactions with key residues W277, R242, and R234 of the POUHD domain even in dynamic conditions. Interestingly, ZINC02145000 and ZINC32124203 established communication not only with the POUHD domain but also with the POUS domain indicating their incredible potency toward thwarting the function of Oct4. ZINC02145000 and ZINC32124203 also reduced the flexibility and escalated the correlations between the amino acid residues of Oct4 evidenced by PCA and DCCM analysis. Finally, our examination proposed two NPIs that can impede the Oct4 function and may help to improve overall survival, diminish tumor relapse, and achieve a cure not only in deadly disease GBM but also in other cancers with minimal side effects.

Interpretations on the Interaction between Protein Tyrosine Phosphatase and E7 Oncoproteins of High and Low-Risk HPV: A Computational Perception.

The most prevalent and common sexually transmitted infection is caused by human papillomavirus (HPV) among sexually active women. Numerous genotypes of HPV are available, among which the major oncoproteins E6 and E7 lead to the progression of cervical cancer. The E7 oncoprotein interacts with cytoplasmic tumor suppressor protein PTPN14, which is the key regulator of cellular growth control pathways effecting the reduction of steady-state level. Disrupting the interaction between the tumor suppressor and the oncoprotein is vital to cease the development of cancer. Hence, the mechanism of interaction between E7 and tumor suppressor is explored through protein-protein and protein-ligand binding along with the conformational stability studies. The obtained results state that the LXCXE domain of HPV E7 of high and low risks binds with the tumor suppressor protein. Also, the small molecules bind in the interface of E7-PTPN14 that disrupts the interaction between the tumor suppressor and oncoprotein. These results were further supported by the dynamics simulation stating the stability over the bounded complex and the energy maintained during postdocking as well as postdynamics calculations. These observations possess an avenue in the drug discovery that leads to further validation and also proposes a potent drug candidate to treat cervical cancer caused by HPV.

Spectroscopic and molecular docking studies for the binding and interaction aspects of curcumin-cysteine conjugate and rosmarinic acid with human telomeric G-quadruplex DNA.

The binding and interaction aspects of potential anticancer ligands like: curcumin-cysteine (CC) and rosmarinic acid (RA) with human telomeric G-quadruplex DNA, a novel anticancer target, have been probed by spectroscopic and molecular docking approach. The circular dichroism study unravels the conformational switching from mixed hybrid to parallel structure for the short sequence of human telomeric G-quadruplex structure in the presence of both the ligands. Further a good correlation for binding affinity has been established from the emission and absorption binding spectrum analysis. Further our spectroscopic and molecular docking studies have suggested that the CC having better binding capability than RA to human telomeric G-quadruplex. The presence of L-cysteine moiety in CC ligand is responsible factor for its binding via both minor as well as major groove of human telomeric G-quadruplex DNA where-as RA binds only via minor groove of telomeric G-DNA.

Experiments and simulation on ZIKV NS2B-NS3 protease reveal its complex folding.

Zika virus has been identified in various body fluids such as semen, urine, saliva, cerebrospinal fluid, and vaginal secretion of an infected individual. The pH of these fluids varies from mildly acidic to mildly alkaline. So it is imperative to understand the impact of these conditions on viral protein functioning. We investigated the NS2B-NS3 protease stability and its activity in different denaturing environments. Finding indicates that NS2B-NS3 protease maintains stability at pH 4.8-8.7. Thus it suggests that the complex remains functionally active to hydrolyze the polyprotein within a diverse environmental condition such as variable pH. Despite a stable structure at a broad pH range, a change in environmental conditions dramatically influence its protease activity. Moreover, it is susceptible to structural transformation leading to increased ß-strand or helix content in the presence of alcohol. This study may help further to understand the folding-function relationship of the general flaviviral protease complex.

Artificial Intelligence, Big Data and Machine Learning Approaches in Precision Medicine & Drug Discovery.

Artificial Intelligence revolutionizes the drug development process that can quickly identify potential biologically active compounds from millions of candidate within a short period. The present review is an overview based on some applications of Machine Learning based tools, such as GOLD, Deep PVP, LIB SVM, etc. and the algorithms involved such as support vector machine (SVM), random forest (RF), decision tree and Artificial Neural Network (ANN), etc. at various stages of drug designing and development. These techniques can be employed in SNP discoveries, drug repurposing, ligand-based drug design (LBDD), Ligand-based Virtual Screening (LBVS) and Structure- based Virtual Screening (SBVS), Lead identification, quantitative structure-activity relationship (QSAR) modeling, and ADMET analysis. It is demonstrated that SVM exhibited better performance in indicating that the classification model will have great applications on human intestinal absorption (HIA) predictions. Successful cases have been reported which demonstrate the efficiency of SVM and RF models in identifying JFD00950 as a novel compound targeting against a colon cancer cell line, DLD-1, by inhibition of FEN1 cytotoxic and cleavage activity. Furthermore, a QSAR model was also used to predict flavonoid inhibitory effects on AR activity as a potent treatment for diabetes mellitus (DM), using ANN. Hence, in the era of big data, ML approaches have been evolved as a powerful and efficient way to deal with the huge amounts of generated data from modern drug discovery to model small-molecule drugs, gene biomarkers and identifying the novel drug targets for various diseases.

Investigating into the molecular interactions of flavonoids targeting NS2B-NS3 protease from ZIKA virus through in-silico approaches.

Zika virus (ZIKV), belongs to the flavivirus genus and Flaviviridae family that associated with serious diseased conditions like microcephaly and other neurological disorders (Guillan-Barré syndrome). As there is no vaccine or therapies available against ZIKV to date. Hence, it is an unmet need to find potential drug candidates and target sites against Zika virus infection. NS2B-NS3 protease making an attractive target for therapeutic intervention in ZIKV infections because of its critical role in hydrolysis of a single polyprotein encoded by Zika virus. Recently, there are some experimental evidence about the flavonoids as Zika virus NS2B-NS3 protease inhibitors. However, molecular interaction between protease complex and inhibitors at atomic levels has not been explored. Here, we have taken the experimentally validated thirty-eight flavonoids inhibitors against NS2B-NS3 protease to examine the molecular interaction using molecular docking and molecular dynamics simulations. We found out few flavonoids such as EGCG and its two derivatives, isoquercetin, rutin and sanggenon O showing interaction with catalytic triad (His51, Asp75, and Ser135) of the active site of NS2B-NS3 protease and found to be stable throughout the simulation. Therefore it is evident that interaction with the catalytic triad playing a vital role in the inhibition of the enzyme activity as a result inhibition of the virus propagation. However these compounds can be explored further for understanding the mechanism of action of these compounds targeting NS2B-NS3 protease for inhibition of Zika virus.

In-silico strategies for identification of potent inhibitor for MMP-1 to prevent metastasis of breast cancer.

Matrix Metalloproteinase-1 (MMP-1) has been often upregulated in advanced breast cancers, known to participate in ECM degradation, migration, invasion, thus leading to metastasis. Due to these effects, the condition is often reported to inversely correlate with survival in advanced breast cancers. In the present study, in-silico method was adopted based on selective non zinc binding inhibitors of MMP-1. ADME properties were predicted for PASS filtered compounds and docking calculations were performed using Glide XP and IFD protocols of Schrodinger program. We identified six ligands as potent inhibitors and validated by observing structures and the interactions of MMP-1. The identified hits were validated using molecular dynamics simulation studies. Electronic structure analysis was performed for two top hit compounds myricetin and quercetin using density function theory (DFT) at B3LYP/6-31**G level to understand their molecular reactivity. Finally, one compound myricetin has emerged as the structurally stable compound with -7.801 kcal/mol and reasonable pose inside the binding site. Molecular dynamics results indicated that myricetin forms a stable interaction with the key amino acid residues such as Glu209, Glu219, Tyr240 and Pro238. In addition, it did not form any binding with the catalytic zinc at its active site. The interaction pattern of myricetin at its substrate binding site exhibited to be potent MMP-1 inhibitor. DFT study also showed that it has more potent inhibitory effect and solubility. These factors altogether show that myricetin could be considered as the best among the compounds evaluated in inhibiting MMP-1 thereby preventing metastasis of breast cancer. Communicated by Ramaswamy H. Sarma.

High-Throughput Screening and Quantum Mechanics for Identifying Potent Inhibitors Against Mac1 Domain of SARS-CoV-2 Nsp3.

SARS-CoV-2 encodes the Mac1 domain within the large nonstructural protein 3 (Nsp3), which has an ADP-ribosylhydrolase activity conserved in other coronaviruses. The enzymatic activity of Mac1 makes it an essential virulence factor for the pathogenicity of coronavirus (CoV). They have a regulatory role in counteracting host-mediated antiviral ADP-ribosylation, which is unique part of host response towards viral infections. Mac1 shows highly conserved residues in the binding pocket for the mono and poly ADP-ribose. Therefore, SARS-CoV-2 Mac1 enzyme is considered as an ideal drug target and inhibitors developed against them can possess a broad antiviral activity against CoV. ADP-ribose-1 phosphate bound closed form of Mac1 domain is considered for screening with large database of ZINC. XP docking and QPLD provides strong potential lead compounds, that perfectly fits inside the binding pocket. Quantum mechanical studies expose that, substrate and leads have similar electron donor ability in the head regions, that allocates tight binding inside the substrate-binding pocket. Molecular dynamics study confirms the substrate and new lead molecules presence of electron donor and acceptor makes the interactions tight inside the binding pocket. Overall binding phenomenon shows both substrate and lead molecules are well-adopt to bind with similar binding mode inside the closed form of Mac1.

Computational analysis identifies druggable mutations in human rBAT mediated Cystinuria.

Culex quinquefasciatus Cqm1 protein acts as the receptor for Lysinibacillus sphaericus mosquito-larvicidal binary (BinAB) toxin that is used worldwide for mosquito control. We found amino acid transporter protein, rBAT, as phylogenetically closest Cqm1 homolog in humans. The present study reveals large evolutionary distance between Cqm1 and rBAT, and rBAT ectodomain lacks the sequence motif which serves as binding-site for the BinAB toxin. Thus, BinAB toxin can be expected to remain safe for humans. rBAT (heavy subunit; SLC3A1) and catalytic b0,+AT (light subunit; SLC7A9), linked by single disulfide bond, mediate renal reabsorption of cystine and dibasic amino acids in Na+ independent manner. Mutations in rBAT cause type I Cystinuria disease which shows global prevalence, and rBAT can be thought as an important pharmacological target. However, 3D structures of rBAT and b0,+AT, the two components of b0,+ heteromeric amino acid transporter systems, are not available. We constructed a reliable homology model of rBAT using Cqm1 coordinates and that of transmembrane b0,+AT subunit using LAT1 coordinates. Mapping of pathogenic mutations onto rBAT ectodomain revealed their scattered distribution throughout the rBAT protein. Further, our computational simulations-based scoring of several known deleterious mutations of rBAT revealed that mutations those do not compromise the protein fold and stability, are localized on the same face of the molecule. These residues are expected to interact with the b0,+AT transporter. The present study thus identifies druggable sites on rBAT that could be targeted for the treatment of type I Cystinuria.Communicated by Ramaswamy H. Sarma.